Non-Contact Video-Based Neonatal Respiratory Monitoring

Respiratory rate (RR) has been shown to be a reliable predictor of cardio-pulmonary deterioration, but standard RR monitoring methods in the neonatal intensive care units (NICU) with contact leads have been related to iatrogenic complications. Video-based monitoring is a potential non-contact system...

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Main Authors: Scott L. Rossol, Jeffrey K. Yang, Caroline Toney-Noland, Janine Bergin, Chandan Basavaraju, Pavan Kumar, Henry C. Lee
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Children
Subjects:
Online Access:https://www.mdpi.com/2227-9067/7/10/171
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spelling doaj-788c98b365004ae0a5410744650421112021-04-02T11:10:35ZengMDPI AGChildren2227-90672020-10-01717117110.3390/children7100171Non-Contact Video-Based Neonatal Respiratory MonitoringScott L. Rossol0Jeffrey K. Yang1Caroline Toney-Noland2Janine Bergin3Chandan Basavaraju4Pavan Kumar5Henry C. Lee6Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USADepartment of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USADepartment of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USADepartment of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USACocoonCam, Sunnyvale, CA 94089, USACocoonCam, Sunnyvale, CA 94089, USADepartment of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94305, USARespiratory rate (RR) has been shown to be a reliable predictor of cardio-pulmonary deterioration, but standard RR monitoring methods in the neonatal intensive care units (NICU) with contact leads have been related to iatrogenic complications. Video-based monitoring is a potential non-contact system that could improve patient care. This iterative design study developed a novel algorithm that produced RR from footage analyzed from stable NICU patients in open cribs with corrected gestational ages ranging from 33 to 40 weeks. The final algorithm used a proprietary technique of micromotion and stationarity detection (MSD) to model background noise to be able to amplify and record respiratory motions. We found significant correlation—<i>r</i> equals 0.948 (<i>p</i> value of 0.001)—between MSD and the current hospital standard, electrocardiogram impedance pneumography. Our video-based system showed a bias of negative 1.3 breaths and root mean square error of 6.36 breaths per minute compared to standard continuous monitoring. Further work is needed to evaluate the ability of video-based monitors to observe clinical changes in a larger population of patients over extended periods of time.https://www.mdpi.com/2227-9067/7/10/171neonatal monitoringrespiratory rateclinical alarmsvideo recordingbiomedical technology
collection DOAJ
language English
format Article
sources DOAJ
author Scott L. Rossol
Jeffrey K. Yang
Caroline Toney-Noland
Janine Bergin
Chandan Basavaraju
Pavan Kumar
Henry C. Lee
spellingShingle Scott L. Rossol
Jeffrey K. Yang
Caroline Toney-Noland
Janine Bergin
Chandan Basavaraju
Pavan Kumar
Henry C. Lee
Non-Contact Video-Based Neonatal Respiratory Monitoring
Children
neonatal monitoring
respiratory rate
clinical alarms
video recording
biomedical technology
author_facet Scott L. Rossol
Jeffrey K. Yang
Caroline Toney-Noland
Janine Bergin
Chandan Basavaraju
Pavan Kumar
Henry C. Lee
author_sort Scott L. Rossol
title Non-Contact Video-Based Neonatal Respiratory Monitoring
title_short Non-Contact Video-Based Neonatal Respiratory Monitoring
title_full Non-Contact Video-Based Neonatal Respiratory Monitoring
title_fullStr Non-Contact Video-Based Neonatal Respiratory Monitoring
title_full_unstemmed Non-Contact Video-Based Neonatal Respiratory Monitoring
title_sort non-contact video-based neonatal respiratory monitoring
publisher MDPI AG
series Children
issn 2227-9067
publishDate 2020-10-01
description Respiratory rate (RR) has been shown to be a reliable predictor of cardio-pulmonary deterioration, but standard RR monitoring methods in the neonatal intensive care units (NICU) with contact leads have been related to iatrogenic complications. Video-based monitoring is a potential non-contact system that could improve patient care. This iterative design study developed a novel algorithm that produced RR from footage analyzed from stable NICU patients in open cribs with corrected gestational ages ranging from 33 to 40 weeks. The final algorithm used a proprietary technique of micromotion and stationarity detection (MSD) to model background noise to be able to amplify and record respiratory motions. We found significant correlation—<i>r</i> equals 0.948 (<i>p</i> value of 0.001)—between MSD and the current hospital standard, electrocardiogram impedance pneumography. Our video-based system showed a bias of negative 1.3 breaths and root mean square error of 6.36 breaths per minute compared to standard continuous monitoring. Further work is needed to evaluate the ability of video-based monitors to observe clinical changes in a larger population of patients over extended periods of time.
topic neonatal monitoring
respiratory rate
clinical alarms
video recording
biomedical technology
url https://www.mdpi.com/2227-9067/7/10/171
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AT janinebergin noncontactvideobasedneonatalrespiratorymonitoring
AT chandanbasavaraju noncontactvideobasedneonatalrespiratorymonitoring
AT pavankumar noncontactvideobasedneonatalrespiratorymonitoring
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